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characterization methods (potentially including electrochemistry, multiple microscopy modalities, quartz microbalance, impedance spectroscopy) as well as surface modification and characterization and protein
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research project (e.g. PhD in physical chemistry, chemical physics, computational chemistry or relevant) and needs to be passionate about research. Experience in usage Gaussian, ADF, Dalton, ORCA etc
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machine learning with applications in science. The aim is to develop novel machine learning and other data driven AI methods for scaling up and improving scientific processes beyond what humans can do, for
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characteristics. Innovate methods for integrating photosynthetic components into material systems and devices with additive manufacturing. Functionalize biological components with technological and stimuli
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: Develop biohybrid living materials and devices based on photosynthetic organisms with responsive and evolving characteristics. Innovate methods for integrating photosynthetic components into material
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properties, and magnon–phonon interactions using quantum mechanical methods. As postdoc, you will principally carry out research. A certain amount of teaching may be part of your duties, up to a maximum of 20
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engineering and mechanical characterization. The following education, experience and expertise are required: PhD in material science, civil engineering, structural Engineering, or a closely related discipline
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these may be taken into consideration. The applicant must hold a PhD in Pediatrics or a related field. As an applicant, you are expected to: Have experience in the analysis of multiomics data and Olink
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these may be taken into consideration. The applicant must hold a PhD in bioinformatics or a related field. As an applicant, you are expected to: Have experience in the analysis of multiomics data and
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curious and motivated postdoc with a PhD in biomedical engineering, physics, materials science, organic chemistry—or similar—and a drive to explore new frontiers in science. 👉 Learn more and apply here